Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to the prior art by inclusion in this section.
Bipartite graphs depict the relationships between two different types of entities. Bipartite graphs are used in a wide range of data visualization and analysis domains. Non-limiting examples of systems that generate graphical displays of bipartite graphs include the automated graphical display of event logs that are recorded during the operation of a motor vehicle that map particular vehicles or vehicle models to sets of mechanical issues, graphical displays of consumers and products that the consumers buy, graphical displays of legislators mapped to bills supported by the legislators, and graphical displays of relationships between users of social media networks and different groups in the social media networks.
While bipartite graphs are useful for visualizing the relationships between entities, more complex bipartite graphs that contain a large number of entities and connections can often be difficult for humans to interpret when these large graphs are depicted on a display screen, printed, or otherwise generated in an automated manner. In particular, many complex graphs that include hundreds, thousands, or even higher numbers of entities and connections can be displayed using modern computing systems. However, the graphical depictions of these bipartite graphs are often extremely cluttered and cannot easily be understood by human users who analyze the graphs. Consequently, improvements to methods and systems that generate graphical depictions of bipartite graphs that improve the generation of graphics representing bipartite graphs to reduce clutter and improve understandability of the graphs would be beneficial.